Neural Dynamics of Motion Segmentation and Grouping

A neural network model of motion segmentation by visual cortex is de(cid:173) scribed. The model clarifies how preprocessing of motion signals by a Motion Oriented Contrast Filter (MOC Filter) is joined to long-range co(cid:173) operative motion mechanisms in a motion Cooperative Competitive Loop (CC Loop) to control phenomena such as as induced motion, motion cap(cid:173) ture, and motion aftereffects. The total model system is a motion Bound(cid:173) ary Contour System (BCS) that is computed in parallel with a static BCS before both systems cooperate to generate a boundary representation for three dimensional visual form perception. The present investigations clari(cid:173) fy how the static BCS can be modified for use in motion segmentation prob(cid:173) lems, notably for analyzing how ambiguous local movements (the aperture problem) on a complex moving shape are suppressed and actively reorga(cid:173) nized into a coherent global motion signal. INTRODUCTION: WHY ARE STATIC AND MOTION BOUNDARY CONTOUR SYSTEMS NEEDED?